Dynamic visual cortical connectivity analysis based on functional magnetic resonance imaging

Abstract

Background: Studies of brain functional connectivity (FC) and effective connectivity (EC) using the functional magnetic resonance imaging (fMRI) have advanced our understanding of functional organization on visual cortex of human brain. The current studies mainly focus on static or dynamic connectivity, while the relationships between them have not been well characterized especially for static EC (sEC) and dynamic EC (dEC), as well as the consistency characteristics of changing trend of dFCs and dECs, which is of great importance to reveal the neural information processing mechanism in visual cortex region. Method: In this study, we explore these relationships among several subareas of human visual cortex (V1–V5) by calculating the connection intensity and information flow among them over time by sliding window method, which are defined by Pearson correlation coefficient and Granger causality analysis, respectively, in each window. Results: The results demonstrate that there are extensive connections existing in human visual network, which are time-varying both in resting and task-related states. sFC intensity is negatively correlated with the variance of dFC, while sEC intensity is positively correlated with the variance of dEC. Furthermore, we also find that dFC within visual cortex at rest shows more consistency, while dEC shows less compared with task state in changing trend. Conclusion: Therefore, this study provides novel findings about dynamics of connectivity in human visual cortex from the perspective of functional and effective connectivity.